IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v33y2014i4p509-533.html
   My bibliography  Save this article

Nonmonotonic Status Effects in New Product Adoption

Author

Listed:
  • Yansong Hu

    (Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom)

  • Christophe Van den Bulte

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

We investigate how the tendency to adopt a new product independently of social influence, the recipients' susceptibility to such influence, and the sources' strength of influence vary with social status. Leveraging insights from social psychology and sociology about middle-status anxiety and conformity, we propose that for products that potential adopters expect to boost their status, both the tendency to adopt independently from others and the susceptibility to contagion is higher for middle-status than for low- and high-status customers. Applying a nested case-control design to the adoption of commercial kits used in genetic engineering, we find evidence that status affects (i) how early or late one adopts regardless of social influence, (ii) how susceptible one is to such influence operating through social ties, and (iii) how influential one's own behavior is in triggering adoption by others. The inverse-U patterns in (i) and (ii) are consistent with middle-status anxiety and conformity. The findings have implications for how to use status to better understand adoption and contagion mechanisms, and for targeting customers when launching new products.

Suggested Citation

  • Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
  • Handle: RePEc:inm:ormksc:v:33:y:2014:i:4:p:509-533
    DOI: 10.1287/mksc.2014.0857
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.2014.0857
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.2014.0857?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Dennis H. Gensch, 1984. "Targeting the Switchable Industrial Customer," Marketing Science, INFORMS, vol. 3(1), pages 41-54.
    2. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    3. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    4. Olivier Toubia & Andrew T. Stephen, 2013. "Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?," Marketing Science, INFORMS, vol. 32(3), pages 368-392, May.
    5. Nailya Ordabayeva & Pierre Chandon, 2011. "Getting Ahead of the Joneses: When Equality Increases Conspicuous Consumption among Bottom-Tier Consumers," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 38(1), pages 27-41.
    6. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    7. Pierre Azoulay & Toby Stuart & Yanbo Wang, 2014. "Matthew: Effect or Fable?," Management Science, INFORMS, vol. 60(1), pages 92-109, January.
    8. Yingda Lu & Kinshuk Jerath & Param Vir Singh, 2013. "The Emergence of Opinion Leaders in a Networked Online Community: A Dyadic Model with Time Dynamics and a Heuristic for Fast Estimation," Management Science, INFORMS, vol. 59(8), pages 1783-1799, August.
    9. Jacob Goldenberg & Barak Libai & Eitan Muller & Stefan Stremersch, 2010. "Database Submission—The Evolving Social Network of Marketing Scholars," Marketing Science, INFORMS, vol. 29(3), pages 561-567, 05-06.
    10. Wendy W. Moe & David A. Schweidel, 2012. "Online Product Opinions: Incidence, Evaluation, and Evolution," Marketing Science, INFORMS, vol. 31(3), pages 372-386, May.
    11. Jonah Berger & Morgan Ward, 2010. "Subtle Signals of Inconspicuous Consumption," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(4), pages 555-569, December.
    12. Christophe Van den Bulte & Raghuram Iyengar, 2011. "Tricked by Truncation: Spurious Duration Dependence and Social Contagion in Hazard Models," Marketing Science, INFORMS, vol. 30(2), pages 233-248, 03-04.
    13. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    14. David Godes, 2011. "Commentary--Invited Comment on "Opinion Leadership and Social Contagion in New Product Diffusion"," Marketing Science, INFORMS, vol. 30(2), pages 224-229, 03-04.
    15. David Bell & Sangyoung Song, 2007. "Neighborhood effects and trial on the internet: Evidence from online grocery retailing," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 361-400, December.
    16. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    17. Sinan Aral, 2011. "Commentary--Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 217-223, 03-04.
    18. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    19. Silvia Bellezza & Francesca Gino & Anat Keinan, 2014. "The Red Sneakers Effect: Inferring Status and Competence from Signals of Nonconformity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(1), pages 35-54.
    20. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    21. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    22. Ran Kivetz & Oleg Urminsky & Yuhuang Zheng, 2006. "The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention," Natural Field Experiments 00658, The Field Experiments Website.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hui-Ju Wang, 2022. "Understanding reviewer characteristics in online reviews via network structural positions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1311-1325, September.
    2. Eggers, Fabian & Risselada, Hans & Niemand, Thomas & Robledo, Sebastian, 2022. "Referral campaigns for software startups: The impact of network characteristics on product adoption," Journal of Business Research, Elsevier, vol. 145(C), pages 309-324.
    3. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    4. Zongshui Wang & Hong Zhao & Yan Wang, 2015. "Social networks in marketing research 2001–2014: a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 65-82, October.
    5. Yingzhao Xiao & Liuyang Xue & David Ahlstrom & Chundong Zheng & Xiling Hao, 2024. "To Conform or Not to Conform? The Role of Social Status and Firm Corporate Social Responsibility," Journal of Business Ethics, Springer, vol. 193(3), pages 655-677, September.
    6. Park, Minjung, 2019. "Selection bias in estimation of peer effects in product adoption," Journal of choice modelling, Elsevier, vol. 30(C), pages 17-27.
    7. Bryan Bollinger & Kenneth Gillingham & A. Justin Kirkpatrick & Steven Sexton, 2022. "Visibility and Peer Influence in Durable Good Adoption," Marketing Science, INFORMS, vol. 41(3), pages 453-476, May.
    8. Anirban Adhikary & Krishna Sundar Diatha & Sourav Bikash Borah & Amalesh Sharma, 2021. "How does the adoption of digital payment technologies influence unorganized retailers’ performance? An investigation in an emerging market," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 882-902, September.
    9. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    10. Valente, Thomas W. & Dyal, Stephanie R. & Chu, Kar-Hai & Wipfli, Heather & Fujimoto, Kayo, 2015. "Diffusion of innovations theory applied to global tobacco control treaty ratification," Social Science & Medicine, Elsevier, vol. 145(C), pages 89-97.
    11. Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
    12. Yuho Chung & Yiwei Li & Jianmin Jia, 2021. "Exploring embeddedness, centrality, and social influence on backer behavior: the role of backer networks in crowdfunding," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 925-946, September.
    13. Pinar Yildirim & Yanhao Wei & Christophe Bulte & Joy Lu, 2020. "Social network design for inducing effort," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 381-417, December.
    14. Onishi Hiroshi, 2018. "Consumers’ Social Learning About Videogame Consoles Through Multiple Website Browsing," Journal of Systems Science and Information, De Gruyter, vol. 6(6), pages 495-511, December.
    15. Raghuram Iyengar & Christophe Van den Bulte & Jae Young Lee, 2015. "Social Contagion in New Product Trial and Repeat," Marketing Science, INFORMS, vol. 34(3), pages 408-429, May.
    16. Viswanathan, Vijay & Sese, F. Javier & Krafft, Manfred, 2017. "Social influence in the adoption of a B2B loyalty program: The role of elite status members," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 901-918.
    17. Liu, Yang & Dong, Jiuyu & Ying, Ying & Jiao, Hao, 2021. "Status and digital innovation: A middle-status conformity perspective," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    18. Sarah Gelper & Ralf van der Lans & Gerrit van Bruggen, 2021. "Competition for Attention in Online Social Networks: Implications for Seeding Strategies," Management Science, INFORMS, vol. 67(2), pages 1026-1047, February.
    19. Gila E. Fruchter & Ashutosh Prasad & Christophe Van den Bulte, 2022. "Too Popular, Too Fast: Optimal Advertising and Entry Timing in Markets with Peer Influence," Management Science, INFORMS, vol. 68(6), pages 4725-4741, June.
    20. Yanhao Wei & Pinar Yildirim & Christophe Van den Bulte & Chrysanthos Dellarocas, 2016. "Credit Scoring with Social Network Data," Marketing Science, INFORMS, vol. 35(2), pages 234-258, March.
    21. Cambra-Fierro, Jesús & Gao, Lily (Xuehui) & Melero-Polo, Iguácel, 2021. "The power of social influence and customer–firm interactions in predicting non-transactional behaviors, immediate customer profitability, and long-term customer value," Journal of Business Research, Elsevier, vol. 125(C), pages 103-119.
    22. Md. Alamgir Hossain & Most. Nirufer Yesmin & Nusrat Jahan & Minho Kim, 2021. "Effects of Service Justice, Quality, Social Influence and Corporate Image on Service Satisfaction and Customer Loyalty: Moderating Effect of Bank Ownership," Sustainability, MDPI, vol. 13(13), pages 1-13, July.
    23. Shuiping Ding & Jie Lin & Zhenyu Zhang, 2020. "Influences of Reference Group on Users’ Purchase Intentions in Network Communities: From the Perspective of Trial Purchase and Upgrade Purchase," Sustainability, MDPI, vol. 12(24), pages 1-18, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raghuram Iyengar & Christophe Van den Bulte & Jae Young Lee, 2015. "Social Contagion in New Product Trial and Repeat," Marketing Science, INFORMS, vol. 34(3), pages 408-429, May.
    2. Nejad, Mohammad G. & Amini, Mehdi & Babakus, Emin, 2015. "Success Factors in Product Seeding: The Role of Homophily," Journal of Retailing, Elsevier, vol. 91(1), pages 68-88.
    3. Florian Probst & Laura Grosswiele & Regina Pfleger, 2013. "Who will lead and who will follow: Identifying Influential Users in Online Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 179-193, June.
    4. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    5. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Rejoinder--Further Reflections on Studying Social Influence in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 230-232, 03-04.
    6. Hinz, Oliver & Schulze, Christian & Takac, Carsten, 2014. "New product adoption in social networks: Why direction matters," Journal of Business Research, Elsevier, vol. 67(1), pages 2836-2844.
    7. Liye Ma & Ramayya Krishnan & Alan L. Montgomery, 2015. "Latent Homophily or Social Influence? An Empirical Analysis of Purchase Within a Social Network," Management Science, INFORMS, vol. 61(2), pages 454-473, February.
    8. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    9. Michael Braun & André Bonfrer, 2011. "Scalable Inference of Customer Similarities from Interactions Data Using Dirichlet Processes," Marketing Science, INFORMS, vol. 30(3), pages 513-531, 05-06.
    10. Xingyu Chen & Xing Li & Dai Yao & Zhimin Zhou, 2019. "Seeking the support of the silent majority: are lurking users valuable to UGC platforms?," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 986-1004, November.
    11. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    12. Nejad, Mohammad G. & Amini, Mehdi & Sherrell, Daniel L., 2016. "The profit impact of revenue heterogeneity and assortativity in the presence of negative word-of-mouth," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 656-673.
    13. Sharad Goel & Daniel G. Goldstein, 2014. "Predicting Individual Behavior with Social Networks," Marketing Science, INFORMS, vol. 33(1), pages 82-93, January.
    14. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    15. Sinan Aral & Dylan Walker, 2014. "Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment," Management Science, INFORMS, vol. 60(6), pages 1352-1370, June.
    16. Kannan, P.K. & Li, Hongshuang “Alice”, 2017. "Digital marketing: A framework, review and research agenda," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 22-45.
    17. Zhang, Yuchi & Moe, Wendy W. & Schweidel, David A., 2017. "Modeling the role of message content and influencers in social media rebroadcasting," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 100-119.
    18. Viswanathan, Vijay & Sese, F. Javier & Krafft, Manfred, 2017. "Social influence in the adoption of a B2B loyalty program: The role of elite status members," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 901-918.
    19. Yaniv Dover & Jacob Goldenberg & Daniel Shapira, 2012. "Network Traces on Penetration: Uncovering Degree Distribution from Adoption Data," Marketing Science, INFORMS, vol. 31(4), pages 689-712, July.
    20. Inyoung Chae & Andrew T. Stephen & Yakov Bart & Dai Yao, 2017. "Spillover Effects in Seeded Word-of-Mouth Marketing Campaigns," Marketing Science, INFORMS, vol. 36(1), pages 89-104, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:33:y:2014:i:4:p:509-533. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.